Multilevel modelling of the geographical distributions of diseases

Multilevel modelling is used on problems arising from the analysis of spatially distributed health data. We use three applications to demonstrate the use of multilevel modelling in this area. The first concerns small area all-cause mortality rates from Glasgow where spatial autocorrelation between residuals is examined. The second analysis is of prostate cancer cases in Scottish counties where we use a range of models to examine whether the incidence is higher in more rural areas. The third develops a multiple-cause model in which deaths from cancer and cardiovascular disease in Glasgow are examined simultaneously in a spatial model. We discuss some of the issues surrounding the use of complex spatial models and the potential for future developments.     

Long memory in intertrade durations,counts and realized volatility of NYSE stocks

We study the persistence of intertrade durations, counts (number of transactions in equally spaced intervals of clock time), squared returns and realized volatility in 10 stocks trading on the New York Stock Exchange. A semiparametric analysis reveals the presence of long memory in all of these series, with potentially the same memory parameter. We introduce a parametric latent-variable long-memory stochastic duration (LMSD) model which is shown to better fit the data than the autoregressive conditional duration model (ACD) in a variety of ways. The empirical evidence we present here is in agreement with theoretical results on the propagation of memory from durations to counts and realized volatility presented in Deo et al. (2009).     

Lack of robustness in time-space disease clustering

The Knox and Mantel procedures of time-space disease clustering are shown to be nonrobust in certain situations. The effect of selecting the necessary constants by a trial-and-error approach drastically alters the nominal significance level. When the population is shifting over time or when the detection rate of the disease is not constant, this artificially induced space-time clustering can increase the probability of rejection to two or more times the nominal significance level.     

Families of power series distributions,with particular reference to the Lerch family

The paper revisits the concept of a power series distribution by defining its series function, its power parameter, and hence its probability generating function. Realization that the series function for a particular distribution is a special case of a recognized mathematical function enables distributions to be classified into families. Examples are the generalized hypergeometric family and the q-series family, both of which contain generalizations of the geometric distribution. The Lerch function (a third generalization of the geometric series) is the series function for the Lerch family. A list of distributions belonging to the Lerch family is provided.     

The effect of area of residence over the life course on subsequent mortality

Summary.  Life course epidemiology concentrates on the contribution that social or physical exposures have across the life course on adult health. It is known that the area of residence can affect health, but little is known about the effect of the area of residence across the life course. We examine the contribution that area of residence in 1960, 1970, 1980 and 1990 made on subsequent mortality for 49736 male inhabitants of Oslo in 1990. We compare the performance of multiple-membership and cross-classified multilevel models on these data with a correlated cross-classified model that was developed for this.     

Seasonal Adjustment of the Weekly Monetary Aggregates: A Model-Based Approach

A procedure is developed for seasonally adjusting weekly time series, based on a composite of regression and time series models. The procedure is applied to some weekly U.S. money supply series currently seasonally adjusted by the Federal Reserve.     

Measuring the efficiency of public services: the limits of analysis

Summary.  Policy makers are increasingly seeking to develop overall measures of the effi-ciency of public service organizations. For that, the use of 'off-the-shelf' statistical tools such as data envelopment analysis and stochastic frontier analysis have been advocated as tools to measure organizational efficiency. The analytical sophistication of such methods has reached an advanced stage of development. We discuss the context within which such models are deployed, their underlying assumptions and their usefulness for a regulator of public services. Four specific model building issues are discussed: the weights that are attached to public service outputs; the specification of the statistical model; the treatment of environmental influences on performance; the treatment of dynamic effects. The paper concludes with recommendations for policy makers and researchers on the development and use of efficiency measurement techniques.     

An EM and a Stochastic Version of the EM Algorithm for Nonparametric Hidden Semi-Markov Models

The Hidden semi-Markov models (HSMMs) were introduced to overcome the constraint of a geometric sojourn time distribution for the different hidden states in the classical hidden Markov models. Several variations of HSMMs were proposed that model the sojourn times by a parametric or a nonparametric family of distributions. In this article, we concentrate our interest on the nonparametric case where the duration distributions are attached to transitions and not to states as in most of the published papers in HSMMs. Therefore, it is worth noticing that here we treat the underlying hidden semi-Markov chain in its general probabilistic structure. In that case, Barbu and Limnios (2008 Barbu , V. , Limnios , N. ( 2008 ). Semi-Markov Chains and Hidden Semi-Markov Models Toward Applications: Their Use in Reliability and DNA Analysis . New York : Springer . [Google Scholar]) proposed an Expectation–Maximization (EM) algorithm in order to estimate the semi-Markov kernel and the emission probabilities that characterize the dynamics of the model. In this article, we consider an improved version of Barbu and Limnios' EM algorithm which is faster than the original one. Moreover, we propose a stochastic version of the EM algorithm that achieves comparable estimates with the EM algorithm in less execution time. Some numerical examples are provided which illustrate the efficient performance of the proposed algorithms.     

中国各地区医疗卫生服务的生产效率分析

医疗卫生是与国民密切相关的一个问题,所以医疗卫生服务的生产效率如何倍受人们的关注。运用DEA模型可以对中国各地区的医疗卫生服务生产效率进行研究,分析不同地区效率高低的原因。结果显示,虽然总体上中国的医疗卫生服务的生产效率处于一个较低水平,但地区之间还是存在着很大的区别,并且地区间即便都是高效率或者低效率的地区,其投入和产出水平也不尽相同。     

Correlated linear models for the analysis of familial correlations

The problems of estimation and hypotheses testing on the parameters of two correlated linear models are discussed. Such models are known to have direct applications in epidemiologic research, particularly in the field of family studies. When the data are unbalanced, the maximum-likelihood estimation of the parameters is achieved by adopting a fairly simple numerical algorithm. The asymptotic variances and covariances of the estimators are derived, and the procedures are illustrated on arterial-blood-pressure data from the literature.     

A statistical analysis of the handling characteristics of certain sporting arms: frontier regression,the moment of inertia,and the radius of gyration

This article applies composed error frontier regression techniques to estimate the minimal moments of inertia and radii of gyration for a unique and varied sample of shotguns. We find that minimum inertia depends on weight, center of gravity, length of pull, and barrel length, but not on gauge, action type, or number of barrels. Curiously, minimal radii of gyration does not depend on barrel length, suggesting that the constraints on these two related but non-identical measures of handling are significantly different despite their high correlation. We also provide evidence in support of G. T. Garwood's claim that a lower inertia, other things equal, is a market-validated characteristic associated with quality.     

长江中游城市群基本公共服务均等化水平测算与区域差异比较

提高基本公共服务均等化水平,是我国"十四五"时期的明确要求。文章利用泰尔指数法对长江中游城市群基本公共服务均等化水平进行测算和比较,得到以下结论:(1)2007—2018年,长江中游城市群基本公共服务的均等化在中等水平但不稳定,均等化水平较高的是基本设施和社会保障,均等化水平较低的是就业服务;(2)"十四五"时期长江中游城市群的基本公共服务均等化水平进入上升期,预计2024年达到优秀水平,但就业和教育文化的均等化仍然维持在较低水平;(3)武汉城市圈对长江中游城市群基本公共服务均等化总差距的贡献最大,武汉城市圈与长株潭"3+5"城市群差距最小,而长株潭"3+5"城市群与合肥都市圈差距最大。     

Computation of final outcome probabilities for the generalised stochastic epidemic

This paper is concerned with methods for the numerical calculation of the final outcome distribution for a well-known stochastic epidemic model in a closed population. The model is of the SIR (Susceptible→Infected→ Removed) type, and the infectious period can have any specified distribution. The final outcome distribution is specified by the solution of a triangular system of linear equations, but the form of the distribution leads to inherent numerical problems in the solution. Here we employ multiple precision arithmetic to surmount these problems. As applications of our methodology, we assess the accuracy of two approximations that are frequently used in practice, namely an approximation for the probability of an epidemic occurring, and a Gaussian approximation to the final number infected in the event of an outbreak. We also present an example of Bayesian inference for the epidemic threshold parameter.     

Ecological regression analysis of environmental benzene exposure and childhood leukaemia: sensitivity to data inaccuracies, geographical scale and ecological bias

Benzene is classified as a group 1 human carcinogen by the International Agency for Research on Cancer, and it is now accepted that occupational exposure is associated with an increased risk of various leukaemias. However, occupational exposure accounts for less than 1% of all benzene exposures, the major sources being cigarette smoking and vehicle exhaust emissions. Whether such low level exposures to environmental benzene are also associated with the risk of leukaemia is currently not known. In this study, we investigate the relationship between benzene emissions arising from outdoor sources (predominantly road traffic and petrol stations) and the incidence of childhood leukaemia in Greater London. An ecological design was used because of the rarity of the disease, the difficulty of obtaining individual level measurements of benzene exposure and the availability of data. However, some methodological difficulties were encountered, including problems of case registration errors, the choice of geographical areas for analysis, exposure measurement errors and ecological bias. We use a Bayesian hierarchical modelling framework to address these issues, and we investigate the sensitivity of our inference to various modelling assumptions.     

Estimability,testability, and connectedness in the cell means model

This article discusses the conocepts of estimation of parameters and tests of linear hyp hypotheses in the fixed effects (ANOVA) model with some zero cell frequencies. The concept of connected experiments is generalized ot he cel1-means model and relatedtotheest imation of and test of hy pothe sesa bout the cell means. A simple test for connectedness is developed as a n atur alre sult of thea nalysis of the constrai nedcell means model. The a nalysis of unconnected experimentsisbriefly discussed. Examples are presented toillustrate the ideas.     

Statistical analysis of the usage of a computer system

This paper is concerned with an empirical investigation of a common and important type of computer system and usage in business applications, viz., querying, updating and modifying a large database. Specifically, it describes the analysis of data collected from such an application and addresses two issues. Firstly, it assesses the applicability of statistical assumptions that underlie certain widely-used queueing theory models for computer systems usage. Secondly, it investigates measures of usage, as well as relationships among them, that may serve as appropriate bases for a pricing scheme for usage of computer systems of the type considered here.     

对分形方法在经济预测领域中应用的研究

文章利用分形方法对经济领域中相互影响的经济量进行预测研究,针对实际应用中分形维数不恒定的问题,提出了两种解决的方案,并通过若干实例体现了分形方法在用于经济预测时的准确性、灵活性和易实现等特点。     

Share equations in econometrics: A story of repression,trustration and dead ends

Share equations play an important role in applied economic research, notably in marketing and demand analysis. Both market shares and budget shares have been used as dependent variables in econometric models which were partly motivated by microeconomic theory. However attempts of econometricians (and other statisticians) to treat share equations adequately led mostly to unsatisfactory approaches: Some researchers although admitting that shares satisfy a sum constraint simply repressed the fact that shares cannot be normally distributed. Some researchers looked in vain for a stochastic specification which at the same time is consistent and allows a flexible covariance structure. Last not least almost nobody has properly taken care of additional problems arising from dynamic share models. The paper discusses these three issues and proposes a possible way out of this dilemma which was first suggested by Aitchison (1982) and has been applied to econometric demand analysis by Considine and Mount (1984). Demandtheoretic implications as well as methods of estimation are discussed. An example using German import data illustrates some of the results. Research for this paper is financially supported by Deutsche Forschungsgemeinschaft, SFB 178 “Internationalisierung der Wirtschaft” at the University of Konstanz. Some results reported in this paper have been achieved jointly with Karl Ringwald whose permission for using unpublished joint work is gratefully acknowledged. Critical remarks by an anonymous referee helped to improve the exposition of the paper.     

陕西省生产性服务业集群效应研究

在工业化和信息化的大背景下,生产性服务业在国家和地区的发展中占有越来越重要的地位,故对陕西省生产性服务业集群效应进行实证研究,研究结果表明：生产性服务业集群对陕西省工业发展的影响明显,影响程度达18%,溢出效应为2.2%,但与中国发达地区相比却差距较大。鉴此,提出针对陕西省发展生产性服务业的具体对策与建议。     

Sequential Estimation of Expectations in the Presence of Trend2

A sequence of independent random variables {Z_n:n≥ 1} with unknown probability distributions is considered and the problem of estimating their expectations {M_n+1: n≥ 1} is examined. The estimation of M_n+1 is based on a finite set {z_k:1≤k≤n}, each z_k being an observed value of Z_k, 1 ≤k≤n, and also based on the assumption that {M_n:n≥ 1} follows an unknown trend of a specified form.